We show that conjoint analysis, a popular multi-attribute preference assessment technique used in market research, is a well suited tool to simultaneously evaluate a multitude of gamut mapping algorithms with a psycho-visual testing load not much higher than in conventional psycho-visual tests of gamut mapping algorithms. The gamut mapping algorithms that we test using conjoint analysis are derived from a master algorithm by choosing different parameter settings. Simultaneously we can also test the influence of additional parameters like gamut size on the perceived quality of a mapping. Conjoint analysis allows us to quantify the contribution of every single parameter value to the perceived quality.
Zofia Barańczuk, Iris Sprow, Peter Zolliker, Joachim Giesen, "Conjoint Analysis of Parametrized Gamut Mapping Algorithms" in Proc. IS&T 16th Color and Imaging Conf., 2008, pp 38 - 43, https://doi.org/10.2352/CIC.2008.16.1.art00008